Sr. Manager, Technical Architect – Enterprise AI Solutions
About The Position
Canadian Solar Inc. is seeking a highly experienced and strategic AI leader to drive the design, architecture, and implementation of enterprise AI solutions across global business operations. This role leads the development of scalable AI platforms, enterprise copilots, automation frameworks, and advanced analytics capabilities supporting Sales, Manufacturing, Supply Chain, Engineering, Finance, Cybersecurity, and Corporate Functions. The ideal candidate combines strong technical depth in AI/ML and enterprise architecture with hands-on experience delivering production-grade AI solutions within large-scale global organizations. This individual will serve as both a technical leader and strategic advisor, helping define the company’s AI roadmap while partnering closely with business executives, IT leadership, and cross-functional teams. This is a senior-level role based in North America with global responsibilities across Canadian Solar business units. Preference to have someone near an office hub.
Requirements
- Bachelor's or master's degree in computer science, Artificial Intelligence, Engineering, Data Science, or related discipline
- 8+ years of experience in enterprise software engineering, solution architecture, AI/ML engineering, or related technical leadership roles
- 3+ years of hands-on experience designing and deploying Generative AI / LLM-based enterprise solutions
- Experience leading enterprise-scale AI transformation initiatives in global organizations
- Strong experience with cloud-native architectures and enterprise integration platforms
- Strong proficiency in Python and modern AI/ML frameworks
- Experience with OpenAI, Anthropic Claude, Google Gemini, Microsoft Copilot Studio, LangChain, Semantic Kernel, or equivalent AI ecosystems
- Experience with vector databases, RAG architectures, AI orchestration frameworks, and prompt engineering
- Experience with TensorFlow, PyTorch, Scikit-learn, or similar frameworks
- Strong understanding of enterprise API integration, microservices, and distributed architectures
- Experience with Docker, Kubernetes, CI/CD pipelines, and DevOps practices
- Familiarity with enterprise security and AI governance requirements
- Experience integrating AI solutions with SAP S/4HANA, Microsoft Dynamics 365, Power Platform, or similar enterprise platforms
- Experience with data engineering technologies including SQL, Spark, Databricks, or equivalent platforms is preferred
Nice To Haves
- Advanced degree preferred
- Industry experience in Renewable Energy, Manufacturing, Industrial Technology, Utilities, Energy Storage, Global Supply Chain Operations preferred
Responsibilities
- Define and lead enterprise AI architecture standards, frameworks, and best practices
- Design scalable AI platforms supporting Generative AI, Agentic AI, Machine Learning, and advanced analytics
- Establish enterprise governance for AI security, compliance, model lifecycle management, and responsible AI adoption
- Partner, collaborate and influence senior leadership to identify high-value AI use cases aligned with business priorities and operational efficiency goals
- Lead the end-to-end design and deployment of enterprise AI solutions and intelligent automation initiatives
- Architect and implement AI-powered copilots, knowledge assistants, and workflow automation solutions
- Integrate AI capabilities into enterprise applications including Microsoft Dynamics 365, SAP S/4HANA, Salesforce, Service Platforms, and custom applications
- Design scalable APIs, microservices, and AI orchestration frameworks
- Lead implementation of enterprise GenAI solutions leveraging platforms such as OpenAI, Anthropic Claude, Google Gemini, Microsoft Copilot Studio, and Azure AI Services
- Design Retrieval-Augmented Generation (RAG) architectures, vector databases, prompt engineering frameworks, and enterprise knowledge management solutions
- Build secure enterprise AI integrations with internal data platforms and business systems
- Evaluate and optimize LLM performance, cost, governance, and scalability
- Collaborate with data engineering teams to establish scalable AI/ML pipelines and data architectures
- Design enterprise-grade MLOps and LLMOps capabilities including CI/CD, monitoring, observability, and model governance
- Ensure reliability, scalability, security, and operational readiness of AI platforms
- Support cloud-native AI deployments across Azure, AWS, and Google Cloud
- Serve as technical lead and mentor for AI engineers, developers, and solution architects
- Partner with business stakeholders across Manufacturing, Sales, Operations, Finance, and Supply Chain to translate business requirements into AI-enabled solutions
- Drive vendor evaluations, proof-of-concepts, and strategic partnerships related to AI technologies
- Communicate technical concepts effectively to both technical and executive audiences
Benefits
- competitive salary
- fully comprehensive benefits
- performance bonus package based on an annual objective achievement
- 401(k) Retirement Plan
- medical/dental/life/disability program
- PTO and sick days
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What This Job Offers
Job Type
Full-time
Career Level
Senior
